doi: 10.7763/IJMLC.2012.V2.125
Classification and Evaluation of High-dimensional Image Indexing Structures
Mohammadreza Keyvanpour1
,
Najva Izadpanah2 ,
- 1Department of Computer Engineering, Alzahra University, Tehran, Iran.
- 2Department of Computer Engineering, Islamic Azad University,Qazvin branch, Qazvin, Iran
- 3Department of Computer Science, University of Southern California, Los Angeles, CA, USA.
Abstract
In the recent years, lots of research on image databases has led to proposition of different kinds of multi-dimensional indexing structures to support similarity search in image database systems. Most of current commercial multi-dimensional image indexing structures cannot manage image data points in high dimensional spaces. Such that sequential scanning of these high-dimensional data points can be faster than using a multi-dimensional indexing structure. Therefore, another class of multi-dimensional indexing structures especially has developed for high-dimensional spaces. Due to importance and variety of high-dimensional indexing structures, we first classified them based on their main idea and then we evaluated them according to suggested design requirements of desired high-dimensional indexing structures. We hope this proposed framework will lead to development of more efficient structures to support similarity search in high-dimensional spaces.
Keywords
- High-dimensional space
- multi-dimensional indexing structure
- image database
How to Cite
Mohammadreza Keyvanpour, Najva Izadpanah, and Haleh Karbasforoushan, "Classification and Evaluation of High-dimensional Image Indexing Structures," International Journal of Machine Learning, vol. 2, no. 3, pp. 252-256, 2012. https://doi.org/10.7763/IJMLC.2012.V2.125
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).